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Frontiers in Neuroscience|March 1, 2021
Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural NetworksCharlotte Frenkel, Martin Lefebvre, David BolIEEE Transactions on Biomedical Circuits and Systems|July 23, 2019
MorphIC: A 65-nm 738k-Synapse/mm <sup>2</sup> Quad-Core Binary-Weight Digital Neuromorphic Processor With Stochastic Spike-Driven Online LearningCharlotte Frenkel, Jean-Didier Legat, David BolIEEE Transactions on Biomedical Circuits and Systems|November 13, 2018
A 0.086-mm <sup>2</sup> 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOSCharlotte Frenkel, Martin Lefebvre, Jean-Didier Legat, et al.Frontiers in Neuroscience|September 9, 2020
Hand-Gesture Recognition Based on EMG and Event-Based Camera Sensor Fusion: A Benchmark in Neuromorphic ComputingEnea Ceolini, Charlotte Frenkel, Sumit Bam Shrestha, et al.Nature Communications|February 11, 2025
The neurobench framework for benchmarking neuromorphic computing algorithms and systemsJason Yik, Korneel Van den Berghe, Douwe den Blanken, et al.Pageof 1